Aims: This study aimed to numerically investigate the induction and sustainment of reentrant ventricular arrhythmias during acute ischemic events. A novel personalization strategy of electrophysiological models is developed based on patients' blood flow maps, allowing to analyze how the shape and distribution of poorly perfused regions affect the propagation of the transmembrane potential.
Methods: We developed a patient-specific electrophysiological model starting from perfusion maps of patients suffering from angina pectoris after an ischemic event. Specifically, we considered a multiscale model, coupling the monodomain equation with a variation of the Ten-Tusscher Panfilov model, that accounts for ionic alterations triggered by an acute ischemic event: hypoxia (reduced supply of oxygen), hyperkalemia (increased extracellular potassium concentration) and acidosis (reduced intracellular pH). Additionally, we partitioned the geometry of the left ventricle using myocardial blood flow maps to represent the tissue heterogeneity of ionic properties, assuming a correlation between the least perfused region and ischemic ionic parameters. In particular, low myocardial blood flow values were associated with severe hypoxia, hyperkalemia and acidosis, while border zones were characterized with intermediate values between healthy and ischemic parameters. The mathematical model was discretized using the finite element method in space and backward differentiation formula in time.
Results: The scenario with the most severe stage of acute myocardial ischemia shows a higher arrhythmic propensity in the largest number of patients. Indeed, the likelihood of inducing a sustained reentrant driver depends on the patient-specific size and shape of the ischemic and border zone areas.
Conclusion: This study introduces a computational strategy that enables arrhythmic risk assessment during the rapid phases of acute myocardial ischemia, which can be hardly measurable in patients. Using the patient's perfusion maps, a new and accurate parameterization of the electrophysiology model can be defined to consider the effects of a local reduced oxygenation on arrhythmic propensity.